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Model‐Free Video Detection and Tracking of Pedestrians and Bicyclists
Author(s) -
Malinovskiy Yegor,
Zheng Jianyang,
Wang Yinhai
Publication year - 2009
Publication title -
computer‐aided civil and infrastructure engineering
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 2.773
H-Index - 82
eISSN - 1467-8667
pISSN - 1093-9687
DOI - 10.1111/j.1467-8667.2008.00578.x
Subject(s) - background subtraction , pedestrian , intersection (aeronautics) , computer science , pedestrian detection , computer vision , artificial intelligence , video tracking , tracking (education) , object detection , object (grammar) , real time computing , transport engineering , segmentation , engineering , pixel , psychology , pedagogy
Pedestrian and bicycle monitoring is quickly becoming an avid area of interest as information regarding pedestrian and bicycle flow is needed not only for developing competent access to particular urban corridors and trails, but also for system optimization scenarios, such as transit system operations and intersection controls. In this article, we present a simple, yet effective method for tracking pedestrian and bicycle objects in a relatively large surveillance area, using ordinary un‐calibrated video images. Object extraction is accomplished via background subtraction, while tracking is accomplished through an inherent characteristic cost function. Composite objects are used as a means of dealing with occlusions. The algorithm is implemented using Microsoft Visual C# and was tested on numerous scenes of varying complexity, resulting in an average count rate of 92.7% at the specified checkpoints.